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MiniMed

Develops automated insulin delivery systems

Principal AI Data Science Engineer - Go-To-Market

Data SciencePosted on Nov 13
Full-timeNorthridge, Los Angeles, CA, USA

About the Job

Requirements

  • A bachelor's degree and at least seven years of relevant experience, or an advanced degree and at least five years of relevant experience, are required.
  • At least five years of experience in data science, analytics, business analytics, operations analytics, customer analytics, insights, or a related field is required, including ownership of complex, cross-functional initiatives.
  • Experience using AI-enabled tools to accelerate analytical workflows, including data investigation, automation, dashboard development, data visualization, or insight generation, is required.
  • Proficiency in Python, R, or a similar programming language is required, with experience applying statistical or machine learning methods to large, complex datasets and business problems.
  • Experience using SQL and modern analytics environments, including dbt, cloud data warehouses, and data visualization platforms, is required.

Responsibilities

  • Develop, validate, monitor, and maintain predictive models and forecasts that assess growth opportunities, revenue potential, customer behavior, market dynamics, and competitive threats.
  • Own customer targeting, prioritization, and tiering methodologies to focus commercial resources on the highest-value opportunities.
  • Quantify market opportunities and evaluate business impact to support investment decisions and strategic initiatives.
  • Translate analytical findings into recommendations that guide resource allocation, launch planning, territory design, and growth priorities.
  • Partner with commercial leaders to improve forecasting accuracy and growth planning using historical performance, market trends, and leading indicators.
  • Build early-warning intelligence to identify underperforming accounts, competitive share shifts, territory opportunities, market changes, adoption trends, and emerging commercial risks.
  • Establish and maintain analytical methodologies that are accurate, explainable, well documented, and responsive to changing market conditions.

Desired Qualifications

  • A master's degree or PhD in data science, analytics, statistics, or another relevant quantitative discipline is preferred.
  • Experience applying natural language processing techniques to business problems is preferred.
  • Experience deploying and maintaining analytical or machine learning models in cloud environments, including knowledge of MLOps practices such as version control, testing, monitoring, and model governance, is preferred.
  • Experience in the medical technology, medical device, or healthcare industry, particularly using customer, provider, market, or sales data to inform commercial strategy, is preferred.
  • Experience developing, validating, monitoring, and interpreting predictive models or forecasts, and translating outputs into actionable business recommendations, is preferred.
  • Experience applying analytics to commercial challenges such as customer segmentation and targeting, revenue forecasting, market opportunity sizing, or resource allocation, is preferred.
  • Experience managing the analytical lifecycle from problem definition and data preparation through implementation, documentation, performance monitoring, and stakeholder communication, is preferred.
  • Ability to communicate complex technical findings as clear, actionable recommendations for business leaders and cross-functional stakeholders is preferred.
  • Ability to work independently and exercise sound judgment regarding data quality, privacy, responsible AI use, and model limitations is preferred.
  • Ability to adapt quickly in a fast-paced, evolving environment as priorities and business needs change is preferred.

About the Company

MiniMed

Develops automated insulin delivery systems

MiniMed develops insulin delivery and automated insulin delivery systems, plus related sensors, pens, and software. Its products couple glucose sensors with pumps or smart pens to automatically adjust insulin or simplify dosing. It differentiates itself with an integrated ecosystem of devices and software and a large share of recurring revenue from sensors, consumables, software and services across more than 80 countries. Its goal is to be a leading global provider of insulin delivery and glucose monitoring solutions that help people with diabetes achieve better glycemic control.

Company size
1,001-5,000
Company stage
IPO
Headquarters
Los Angeles, CA
Founded
1983

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